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Description / Abstract
Submitted to the Department of Mathematics and Computer Science in partial fulfillment of the requirements for the degree of Bachelor of Science
Many wildland fire researchers are challenged to get an accurate burn acreage estimates of a wildland fire due to technology limitations. This research aids wildland fire researchers in determining the accuracy of mapping wildland fires by using sUAS (small Unmanned Aircraft System) imagery when comparing hyperspatial to sUAS imagery resampled to satellite scale resolution in. This project made the assumption that sUAS burn extent data was accurate. This assumption allowed for the resampled training data using fuzzy logic control as the method for improving satellite resolution data. The results showed that even though the resolution of imagery significantly drops, the accuracy of the burn extent remains relatively high throughout the burned area. Although sUAS imagery is likely more accurate given its resolution, acquiring satellite imagery is much more time efficient, cost efficient, and has a consistent history of clean data which serves as a great asset towards mapping wildland fire compared to sUAS imagery. This thesis compares the accuracy of satellite imagery and sUAS imagery for wildland fire mapping.Download this Resource
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Copyright NotesNon-exclusive right to publish on file at NNU Library. Available on request.
KeywordsWildland fire extent, Landsat, small Unmanned Aircraft Systems, sUAS
Degree AwardedBachelor of Science
Awarding InstitutionNorthwest Nazarene University
Committee MembersPeter R. Robichaud, Barry L. Myers
Supervisor or ChairDale Hamilton
Peer Reviewed?No
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NNU Computer Science Theses
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